Making the best of a bad situation: Using side effects to reveal new targets for old drugs

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Samuel Lunenfeld Research Institute, Mt. Sinai Hospital, Toronto, Canada, July 25, 2008

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Making the best of a bad situation: Using side effects to reveal new targets for old drugs

  1. 1. Making the best of a bad situation Using side effects to reveal new targets for old drugs Lars Juhl Jensen EMBL Heidelberg
  2. 2. the problem
  3. 3. two drugs
  4. 4. do they share a target?
  5. 5. chemical similarity
  6. 6. Tanimoto coefficients
  7. 9. similar drugs share targets
  8. 10. only trivial predictions
  9. 11. the idea
  10. 12. chemical perturbations
  11. 13. phenotypic readout
  12. 14. drug treatment
  13. 15. side effects
  14. 16. the implementation
  15. 17. information on side effects
  16. 18. package inserts
  17. 20. text mining
  18. 21. side-effect ontology
  19. 22. backtracking
  20. 24. side-effect correlations
  21. 26. GSC weighting
  22. 27. side-effect frequencies
  23. 29. raw similarity score
  24. 31. p-values
  25. 33. side-effect similarity
  26. 34. chemical similarity
  27. 36. reference set
  28. 37. drug–target pairs
  29. 39. drug–drug pairs
  30. 40. score bins
  31. 41. benchmark
  32. 43. fit calibration function
  33. 45. probabilistic scores
  34. 46. the results
  35. 47. drug–drug network
  36. 49. categorization
  37. 54. map onto score space
  38. 56. the experiments
  39. 57. 20 drug–drug relations
  40. 58. in vitro binding assays
  41. 62. K i <10 µM for 11 of 20
  42. 63. cell assays
  43. 64. 9 of 9 showed activity
  44. 66. the future
  45. 67. drug–target relations
  46. 69. Acknowledgments <ul><li>Monica Campillos </li></ul><ul><li>Michael Kuhn </li></ul><ul><li>Anne-Claude Gavin </li></ul><ul><li>Peer Bork </li></ul>
  47. 70. http://larsjuhljensen.wordpress.com

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